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iML1515, a knowledgebase that computes Escherichia coli traits

Nature Biotechnology volume 35, pages 904–908 (2017)Cite this article

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Extracting knowledge from the many types of big data produced by high-throughput methods remains a challenge, even when data are from Escherichia coli, the best characterized bacterial species. Here, we present iML1515, the most complete genome-scale reconstruction of the metabolic network in E. coli K-12 MG1655 to date, and we demonstrate how it can be used to address this challenge. Enabling analysis of several data types, including transcriptomes, proteomes, and metabolomes, iML1515 accounts for 1,515 open reading frames and 2,719 metabolic reactions involving 1,192 unique metabolites. The iML1515 knowledgebase is linked to 1,515 protein structures to provide an integrated modeling framework bridging systems and structural biology. We apply iML1515 to build metabolic models of E. coli human gut microbiome strains from metagenomic sequencing data. We then use iML1515 to build metabolic models for E. coli clinical isolates and predict their metabolic capabilities. Finally, we use iML1515 to carry out a comparative structural proteome analysis of 1,122 E. coli strains and identify multi-strain sequence variations.

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Figure 1: iML1515 genome-scale reconstruction.
Figure 2: Model validation.
Figure 3: Application of iML1515 for clinical isolates and metagenomes.
Figure 4: Comparison of iML1515 to sequence variations in 1,122 clinical isolates of E. coli.

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Acknowledgements

We would like to thank D. Zielinski, J. Lerman, J. Orth, S. Bowen, and J. Reed for helpful discussions. We'd like to thank M. Abrams for copyediting help. The work was funded by the Novo Nordisk Foundation (Grant NNF10CC1016517) and by grant 1R01GM057089 from the NIH/NIGMS and 1-U01-AI124316-01 from NIH/NIAID. B.O.P., C.J.L., and A.M.F. received support from the Novo Nordisk Foundation Center for Biosustainability (NNF10CC1016517).

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Author notes

  1. Jonathan M Monk, Colton J Lloyd and Elizabeth Brunk: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Bioengineering, University of California, San Diego, La Jolla, California, USA

    Jonathan M Monk, Colton J Lloyd, Elizabeth Brunk, Nathan Mih, Anand Sastry, Zachary King, Zhen Zhang, Adam M Feist & Bernhard O Palsson

  2. Graduate School of Biological Sciences Nara Institute of Science and Technology, Ikoma, Nara, Japan

    Rikiya Takeuchi, Wataru Nomura & Hirotada Mori

  3. The NNF Center for Biosustainability, The Technical University of Denmark, Lyngby, Denmark

    Adam M Feist & Bernhard O Palsson

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  1. Jonathan M Monk
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Supplementary information

Supplementary Figures Tables and Texts

Supplementary Figures 1–10, Supplementary Tables 1–4, Supplementary Methods and Supplementary Notes 1–7 (PDF 2544 kb)

Supplementary Data set 1

All models in SBML and JSON format (ZIP 3239 kb)

Supplementary Data set 2

Model statistics (XLSX 1008 kb)

Supplementary Data set 3

ROS generating reactions (XLSX 9302 kb)

Supplementary Data set 4

TF Barcode information (XLSX 1073 kb)

Supplementary Data set 5

ALE data for GAM/NGAM calculations (XLSX 13 kb)

Supplementary Data set 6

iML1515 GEM-PRO (XLSX 487 kb)

Supplementary Data set 7

dGPR network in cytoscape format (ZIP 935 kb)

Supplementary Data set 8

iML1515 dGPR Cytoscape Map (PDF 473 kb)

Supplementary Data set 9

OMICs Data Mapping (XLSX 112 kb)

Supplementary Data set 10

Master phenotype database (XLSX 31077 kb)

Supplementary Data set 11

All essential predictions (XLSX 4690 kb)

Supplementary Data set 12

iML-iso (XLSX 262 kb)

Supplementary Data set 13

Gene conservation (XLSX 37116 kb)

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Monk, J., Lloyd, C., Brunk, E. et al. iML1515, a knowledgebase that computes Escherichia coli traits. Nat Biotechnol 35, 904–908 (2017). https://doi.org/10.1038/nbt.3956

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